Effective Adaptive Iteration Algorithm for Frequency Tracking and Channel Estimation in OFDM Systems
學年 98
學期 2
出版(發表)日期 2010-05-01
作品名稱 Effective Adaptive Iteration Algorithm for Frequency Tracking and Channel Estimation in OFDM Systems
作品名稱(其他語言)
著者 Liu, Hong-Yu; Yen, R.Y.
單位 淡江大學電機工程學系
出版者 Piscataway: Institute of Electrical and Electronics Engineers
著錄名稱、卷期、頁數 IEEE Transactions on Vehicular Technology 59(4), pp.2093-2097
摘要 For joint maximum-likelihood (ML) frequency tracking and channel estimation using orthogonal frequency-division multiplexing (OFDM) training blocks in OFDM communications over mobile wireless channels, a major difficulty is the local extrema or multiple-solution complication arising from the multidimensional log-likelihood function. To overcome this, we first obtain crude ML frequency-offset estimators using single-time-slot samples from the received time-domain OFDM block. These crude frequency estimators are shown to have unique closed-form solutions. We then optimally combine these crude frequency estimators in the linear-minimum-mean-square-error (LMMSE) sense for a more accurate solution. Finally, by alternatively updating the LMMSE frequency estimator and the ML channel estimator through adaptive iterations, we successfully avoid the use of a multidimensional log-likelihood function, hence obviating the complex task of global solution search and, meanwhile, achieve good estimation performance. Our estimators have mean square errors (MSEs) tightly close to Cramer-Rao bounds (CRBs) with a wide tracking range.
關鍵字
語言 en
ISSN 0018-9545
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Yen, R.Y.
審稿制度
國別 USA
公開徵稿
出版型式 紙本
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